---
library_name: transformers
base_model: cardiffnlp/twitter-xlm-roberta-base-hate-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MultiPRIDE-DualEncoder-LPFT-es
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MultiPRIDE-DualEncoder-LPFT-es

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-hate-spanish](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-hate-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4688
- Accuracy: 0.8030
- F1: 0.5667
- Precision: 0.425
- Recall: 0.85

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6778        | 1.0   | 77   | 0.5634          | 0.8030   | 0.5    | 0.4062    | 0.65   |
| 0.6517        | 2.0   | 154  | 0.5011          | 0.7273   | 0.4706 | 0.3333    | 0.8    |
| 0.6283        | 3.0   | 231  | 0.5121          | 0.7727   | 0.5312 | 0.3864    | 0.85   |
| 0.6041        | 4.0   | 308  | 0.4802          | 0.8182   | 0.5862 | 0.4474    | 0.85   |
| 0.6153        | 5.0   | 385  | 0.4840          | 0.7879   | 0.5484 | 0.4048    | 0.85   |
| 0.5638        | 6.0   | 462  | 0.4761          | 0.7803   | 0.5397 | 0.3953    | 0.85   |
| 0.5421        | 7.0   | 539  | 0.4688          | 0.8030   | 0.5667 | 0.425     | 0.85   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1